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Advanced research methods UNIsa > IRM in review > Flashcards

IRM in review Flashcards

Recap of Introductory research methods

1
Q

What are the 2 types of data analysis?

A

Quantitative methods & Qualitative methods

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2
Q

Testing theories using numbers

A

Quantitative methods

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3
Q

Testing theories using behavior/ language

A

Qualitative methods

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4
Q

The research process

A

data-Initial observation (research question)-generate theory-generate hypotheses-identify variables-collect data and test theory-measure variables-analyse data-graph data-fit to model

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5
Q

What are the 2 types of measurement

A

Categorical & Continuous

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6
Q

Entities are divided into distinct categories

A

Categorical

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7
Q

Entities get a distinct score

A

Continuous

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8
Q

Discrepancy between the actual value we’re trying to measure, and the number we use to represent the value

A

Measurement error

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9
Q

Approaches to design

A

Non-experimental research, Experimental research,

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10
Q

Observe what naturally goes on in the world without directly interfering with it.

A

Non-experimental research

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11
Q

One or more variable is systematically manipulated to see their effect (alone or in combination with) on an outcome variable

A

Experimental research

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12
Q

Allows us to make statements about cause and effect

A

Experimental research

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13
Q

What are the 2 experimental designs?

A

Independent & Repeated-mesures

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14
Q

Between-group/subjects is what experimental design?

A

Independent

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15
Q

Within-subjects is what kind of experimental design?

A

Repeated measures.

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16
Q

Different entities in experimental conditions

A

Between-group/ subjects.

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17
Q

The same entities take part in all experimental conditions

A

Within-subjects

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18
Q

First two steps of data ana?

A

Explore and describe

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19
Q

mean

A

average score in your data

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20
Q

The middle score of an ordered set

A

Median

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21
Q

most frequent score

A

Mode

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22
Q

What is the typical score called?

A

Central tendency

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23
Q

symmetrical distribution is when…

A

The mean, mode and median are roughly the same.

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23
Q

skewed distribution is when…

A

mean, median and mode are different

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24
Q

what are the different modes you can have in the same variable.

A

bimodal and multimodal

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25
Q

A graph plotting values of observations on the horizontal axis, with a bar showing how many times each value occurred in the data set

A

Histogram

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26
Q

normal distribution is

A

bell-shaped and symmetrical around the centre

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27
Q

properties of frequency distribution

A

skew and kurtosis

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28
Q

symmetry of distri bution

A

skew

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29
Q

Frequent scores are clustered at lower end with the tail pointing towards high values ie tail point to positive

A

Positive skew

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30
Q

Frequent scores clustered at higher end with tail pointing toward low values, ie tail points to negative.

A

Negative skew

31
Q

Degree to which scores cluster in the tails.

A

Kurtosis

32
Q

____means there is a positve kutosis, ie >0 distribution is too peaked.

A

Leptokurtic

33
Q

____means there is negative kurtosis, ie <0 distribution is too flat

A

Platykurtic

34
Q

when we desire a normal distribution

A

Normality

35
Q

what are the two types of variance

A

parametric and categorical

36
Q

Standard deviation, range

A

Parametric

36
Q

how to check for normality of a histogram

A

is it bell-shaped, is the distribution symmetrical?

36
Q

standard deviation is nonsense so use a ratio

A

Categorical

37
Q

how to check normality of mean, median and mode?

A

are they roughly equal

38
Q

how to check normality of trimmed mean

A

is the mean similar if you drop the top and bottom 5% of scores?

39
Q

how to check for normality of skewness and kurtosis

A

when divided by standard error is it =0

40
Q

how to check for normality

A

Histogram, mean median, mode, trimmed mean, skewness and kurtosis
outliers.

41
Q

how do I check for outliers.

A

box plot

42
Q

how to screen multiple variables

A

homoscedasticity and heteroscedasticity

43
Q

___are a form of standardization

A

Z-score

44
Q

The most frequently occurring score in a variable is the….

A

Mode

45
Q

A histogram shows that data in your variable has two “peaks’ rather than a single bell-shape. This is indication of a…

A

bimodal distribution

46
Q

A histogram shows that data in your variable is bell-shaped and symmetrical around the center. this is indication of a….

A

Normal distribution.

47
Q

When screening the relationship between two variable, scores in a scatterplot tend to be related similarly at low and high values. this is a sign of…

A

Homoscedasticity

48
Q

The relationship between two variables seesm to differ at different points in the scatterplot. (e.g) this is a sign of…

A

heteroscedasticity

49
Q

A histogram shows that data in your variable is mostly clustered at the high end of values. This is indication of a…

A

Negative skew

50
Q

Most of your scores are not dramatically higher or lower than the mean. This would be indicative of…

A

low standard deviation

51
Q

A histogram shows that data in your variable has five ‘peaks’ rather than a single bell-shape. This is indication of a…

A

multimodal distribution

52
Q

Values vary quite dramatically either side of the mean. This would be indicative of…

A

high standard deviation

53
Q

A histogram shows that data in your variable is mostly clustered at the low end of values. This is indication of a…

A

positive skew

54
Q

measuring the extent to which two variables are related and measures the pattern of responses actoss two variables.

A

Correlation

55
Q

The middle score in an ordered set of data is the…

A

median

56
Q

Assesses the linear relationship between continuous variables.

A

Correlation.

57
Q

Assumptions of correlation

A

Linerarity, normality, continuous variables, homoscedasticity.

58
Q

Possibilty of a third variable.

A

Tertium quid

59
Q

Measures the relationship between two variables, controlling for the effect that a third variable has on them

A

Partial correlation

60
Q

Measures the relationship between two variables controlling for the effect that a third variable has on only one of the others.

A

semi-partial correlation.

61
Q

Its important to ____ _____ ____ because * Reports the magnitude
* There may be a relationship but it might not mean much.

A

measuring affect size

62
Q

As the value of one variable increases, the value of the other variable also increases.

A

Positive correlation.

63
Q

As the value of on variable increases the value of the other variable decreases

A

Negative correlation.

64
Q

strength of the correlation is the R value not the P value. T or F

A

True

65
Q

When looking at effect size the R is…

A

Pearsons product-moment correlation coefficient.

66
Q

when r is +.1 = small effect, .3 = medium effect and .5 large effect . t or f

A

true

67
Q

r2 is….

A

Coefficient of determination.

68
Q

by ___ the value of r you get the amount of variance in one variable that is shared by the other

A

squaring.

69
Q

test the significance of the difference between means

A

t-tests

70
Q

compares two means based on related data e.g. data from the same people measured at different times or data from matched samples.

A

dependent or paired samples t-tests

71
Q

compares two means based on independent data e.g. data from different groups of people

A

Independent-samples t-test.

72
Q

what are the assumptions for t-tests

A

normally distributed scored on the DV and variability of scores on the DV is similar for the two categories of IV

73
Q
A

Advanced research methods UNIsa (5 decks)

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